High Reproducibility Research Articles

Periodic Open Cellular Structures in Chemical Engineering: Application in Catalysis and Separation Processes.

Periodic open cellular structures (POCS) represent a promising new class of structured internals as next-generation catalyst supports in reactors or structured packing elements in separation columns. POCS feature a well-defined morphology and can be fabricated with high reproducibility even for complex geometries by means of additive manufacturing. This results in a uniform and easily controllable flow field, which allows for adjusting the heat and mass transport processes to realize optimal process conditions. We review the fundamentals of POCS, including design and manufacturing as well as transport phenomena for single- and multiphase systems. Moreover, we review recent POCS applications in reaction and separation processes and consider promising future application fields. The exceptional transport characteristics of POCS facilitate the design of highly efficient, flexible, resilient, and safe processes, which is key for achieving process intensification toward a sustainable future.

Engineering the nanozyme hydrogel beads by polyvinyl alcohol/chitosan encapsulation with recyclable and sustainable catalytic activity for visual analysis of hydrogen peroxide

BackgroundHydrogen peroxide (H2O2) plays a vital role in human health and have been regarded as a crucial analyte in metabolic processes, redox transformations, foods research and medical fields. Especially, the long-time and excessive digestion of H2O2 may even cause severe diseases. Although conventional instrumental methods and nanozymes-based colorimetric methods have been developed to accomplish the quantitative analysis of H2O2, the drawbacks of instrument dependence, cost-effectiveness, short lifespan, non-portable and unsustainable detection efficacies will limit their applications in different detection scenarios. ResultsHerein, to address these challenges, we have proposed a novel strategy for nanozyme (RuO2) hydrogel preparation by the solid support from cross-linked polyvinyl alcohol (PVA) and chitosan (CS) to both inherit the dominant peroxidase-like (POD) activity and protect the RuO2 from losing efficacies. Taking advantages from the hydrogel, the encapsulated RuO2 were further prepared as the regularly spherical beads (PCRO) to exhibit the sustainable, recyclable, and robust catalysis. Moreover, the intrinsic color interferences which originated from RuO2 can be avoided by the encapsulation strategy to promote the detection accuracy. Meanwhile, the high mechanical strength of PCRO shows the high stability, reproducibility, and cyclic catalysis to achieve the recyclable detection performance and long lifetime storage (40 days), which enables the sensitively detection of H2O2 with the detection limit as lower to 15 μM and the wide detection linear range from 0.025 to 1.0 mM. SignificanceOn the basis of the unique properties, PCRO has been further adopted to construct a smartphone detection platform to realize the instrument-free and visual analysis of H2O2 in multi-types of milk and real water samples through capturing, processing, and analyzing the RGB values from the colorimetric photographs. Therefore, PCRO with the advanced detection efficacies holds the great potential in achieving the portable and on-site analysis of targets-of-interest.

Preparation of dicationic ionic liquid modified silica stationary phase for mixed-mode liquid chromatography and its application for food additive detection

BackgroundFood safety has become an essential aspect of public concern and there are lots of detection means. Liquid chromatography plays a dominating role in food safety inspection because of its high separation efficiency and reproducibility. However, with the increasing complexity of real samples and monitoring requirements, conventional single-mode chromatography would require frequent column replacement and cannot separate different kinds of analytes on a single column simultaneously, which is costly and time-consuming. There is a great need for fabricating mixed-mode stationary phases and validating the feasibility of employing mixed-mode stationary phases for food safety inspection. ResultsThis work fabricated multifunctional stationary phases for liquid chromatography to determine diverse food additives under the mixed mode of RPLC/HILIC/IEC. Two dicationic ionic liquid silanes were synthesized and bonded onto the silica gel surface. The functionalized silica was characterized by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and elemental analysis. Both columns provide satisfactory separation performance towards 6 hydrophilic nucleosides, 4 hydrophobic polycyclic aromatic hydrocarbons, and 5 anions. Great repeatability of retention (RSD <0.1 %) and column efficiency (100330 plate/m) were obtained. Thermomechanical analysis and linear solvation energy relationship investigated the retention mechanism. Finally, the better in two prepared columns was employed to separate and determine the contents of NO2− and NO3− in vegetables(highest 4906 mg kg−1 NO3− in spinach), preservatives in bottled beverages (180.8 mg kg−1 sodium benzoate in soft drink), and melamine in milk with satisfactory performance and recovery rates ranging from 96.4 % to 105.6 %. SignificanceThis work developed a novel scheme for preparing mixed-mode stationary phases by dicationic ionic liquid which provides great separation selectivity. Most importantly, this work proved the superiority of employing mixed-mode stationary phases for food safety inspection, which might avoid high-cost and frequent changes of columns and chromatography systems in the near future.

Superparamagnetic hydrophilic molecularly imprinted nanoparticles for an efficient and selective removal of tetracycline from water

In this work, a novel superparamagnetic hydrophilic molecularly imprinted nanomaterial for the removal of tetracycline (TC) was synthesized utilizing magnetite (Fe3O4) as the magnetic core, TC as the template molecule, 3-aminopropyltriethoxysilane (APTES) as the functional monomer, and tetraethoxysilane (TEOS) as the cross-linker. Initially, Fe3O4 magnetic nanoparticles (MNP) coated with SiO2 (MNP@SiO2) were synthesized, followed by TC molecular imprinting on the nanoparticles. Initially, Fe3O4 MNP coated with SiO2 (MNP@SiO2) were synthesized, followed by TC molecular imprinting on the nanoparticles. The synthesis method for MNP@SiO2 was optimized, and DLS analysis of 10 replicates showed a nanoparticle size of 70.1 ± 5.8 nm, indicating high method reproducibility. The MNP@SiO2, as well as the imprinted (MNP@SiO2-MIP) and non-imprinted (MNP@SiO2–NIP) nanomaterials, were characterized by FTIR, TEM, VSM, XRD, DLS, Z potential, and BET analysis. The saturation magnetization (Ms) values were 43 emu/g for MNP@SiO2 and 32 emu/g for both MNP@SiO2-MIP and MNP@SiO2–NIP, confirming suitability for magnetic separation using external magnets. Batch binding experiments conducted in water and methanol assessed adsorption isotherms and binding kinetics, with data fitting the Langmuir isotherm model better than the Freundlich model. The developed MIP exhibited significant selectivity against other molecules with similar functional groups and size. In water, the adsorption capacity of the MNP@SiO2-MIP was 23 mg/g, with an imprinting factor of 2.2. Furthermore, the MIP demonstrated good regeneration performance. The material was tested on TC-spiked tap water samples, achieving 80.1 % TC removal with high reproducibility (3.2 %, n = 3). Combining hydrophilic superparamagnetic nanoparticles with molecular imprinting enhances their potential applications in environmental remediation, antibiotic purification, and drug delivery.

Advanced functional materials as reliable tools for capturing food-derived peptides to optimize the peptidomics pre-treatment enrichment workflow.

Peptidomics strategies with high throughput, sensitivity, and reproducibility are key tools for comprehensively analyzing peptide composition and potential functional activities in foods. Nevertheless, complex signal interference, limited ionization efficiency, and low abundance have impeded food-derived peptides' progress in food detection and analysis. As a result, novel functional materials have been born at the right moment that could eliminate interference and perform efficient enrichment. Of note, few studies have focused on developing peptide enrichment materials for food sample analysis. This work summarizes the development of endogenous peptide, phosphopeptide, and glycopeptide enrichment utilizing materials that have been employed extensively recently: organic framework materials, carbon-based nanomaterials, bio-based materials, magnetic materials, and molecularly imprinted polymers. It focuses on the limitations, potential solutions, and future prospects for application in food peptidomics of various advanced functional materials. The size-exclusion effect of adjustable aperture and the modification of magnetic material enhanced the sensitivity and selectivity of endogenous peptide enrichment and aided in streamlining the enrichment process and cutting down on enrichment time. Not only that, the immobilization of metal ions such as Ti4+ and Nb5+ enhanced the capture of phosphopeptides, and the introduction of hydrophilic groups such as arginine, L-cysteine, and glutathione into bio-based materials effectively optimized the hydrophilic enrichment of glycopeptides. Although a portion of the carefully constructed functional materials currently only exhibit promising applications in the field of peptide enrichment for analytical chemistry, there is reason to believe that they will further advance the field of food peptidomics through improved pre-treatment steps.

Estimating the dynamics of greenhouse gas emission during black soldier fly larvae growth under controlled environmental conditions

Edible insects are considered a sustainable alternative protein source. Several studies have indicated that greenhouse gas (GHG) emissions from insects are generally low. These data were usually recorded in closed static chambers, which did not reflect the actual rearing conditions. On the other hand, open respiration chambers need high amounts of substrate and insects, making the analyses time consuming and expensive. In the present study, a novel small-scale open gas exchange recording system for evaluation of GHG emissions from insects is presented. The device consists of four independent respiration chambers, each one equipped with a pump for supplying air, a flow meter and a septum for sampling the flowing air. A validation experiment was carried out using black soldier fly larvae as model organisms and moistened chicken feed (dry matter 40%) as rearing substrate. Three independent runs were conducted, each with two replicates, using 200 neonates larvae and 300 g of substrate. Moistened chicken feed (300 g) without larvae was used as control. Throughout the 12 days rearing period, gas sampling occurred every 12 h. Data interpolation considering a linear tendency between two successive sampling points was applied and overall amounts of gases were quantified as area under the curve. Irrespective of the run, CO2 emissions in the insect-substrate systems increased during the initial 7 d of experiment, consistently followed by a rapid decrease. Multiple cross correlation analysis showed high reproducibility (r ≥ 0.9), while significant differences in the CO2 emissions between insects-substrate system (range 7.76–11.88 g g−1 dry insects) and sole substrate (range 0.20–0.33 g g−1 initial dry substrate) were observed. Very limited N2O (≤1.13 mg g−1 dry insects) and CH4 (≤1.33 mg g−1 dry insects) emissions were detected in this experiment, indicating that the performed black soldier fly larvae rearing did not result in significant production of these GHGs. Overall, the experiment showed that the novel device may be particularly suited for quick and reliable estimation of GHG emissions from edible insects.

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome.

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

A map of glycation and glycoxidation sites in collagen I of human cortical bone: Effects of sex and type 2 diabetes

Complications of diabetes is a major health problem affecting multiple organs including bone, where the chronic disease increases the risk of fragility fractures. One hypothesis suggests a pathogenic role for hyperglycemia-induced modification of proteins, a.k.a. advanced glycation end products (AGEs), resulting in structural and functional damage to bone extracellular matrix (ECM). Evidence supporting this hypothesis has been limited by the lack of comprehensive information about the location of AGEs that accumulate in vivo at specific sites within the proteins of bone ECM. Analyzing extracts from cortical bone of cadaveric femurs by liquid chromatography tandem mass spectrometry, we generated a quantitative AGE map of human collagen I for male and female adult donors with and without diabetes. The map describes the chemical nature, sequence position, and levels of four major physiological AGEs, e.g. carboxymethyllysine, and an AGE precursor fructosyllysine within the collagen I triple-helical region. The important features of the map are: 1) high map reproducibility in the individual bone extracts, i.e. 20 male and 20 female donors; 2) localization of modifications to distinct clusters: 10 clusters containing 34 AGE sites in male donors and 9 clusters containing 28 sites in female donors; 3) significant increases in modification levels in diabetes at multiple sites: 26 out of 34 sites in males and in 17 out of 28 sites in females; and 4) generally higher modification levels in male vs. female donors. Moreover, the AGE levels at multiple individual sites correlated with total bone pentosidine levels in male but not in female donors. Molecular dynamics simulations and molecular modeling predicted significant impact of modifications on solvent exposure, charge distribution, and hydrophobicity of the triple helix as well as disruptions to the structure of collagen I fibril. In summary, the AGE map of collagen I revealed diabetes-induced, sex-specific non-enzymatic modifications at distinct triple helical sites that can disrupt collagen structure, thus proposing a specific mechanism of AGE contribution to diabetic complications in human bone.

Robust data-driven segmentation of pulsatile cerebral vessels using functional magnetic resonance imaging.

Functional magnetic resonance imaging (fMRI) captures rich physiological and neuronal information that can offer insights into neurofluid dynamics, vascular health, and waste clearance function. The availability of cerebral vessel segmentation could facilitate fluid dynamics research in fMRI. However, without magnetic resonance angiography scans, cerebral vessel segmentation is challenging and time-consuming. This study leverages cardiac-induced pulsatile fMRI signal to develop a data-driven, automatic segmentation of large cerebral arteries and the superior sagittal sinus (SSS). The method was validated in a local dataset by comparing it to ground truth cerebral artery and SSS segmentations. Using the Human Connectome Project (HCP) aging dataset, the method's reproducibility was tested on 422 participants aged 36 to 100 years, each with four repeated fMRI scans. The method demonstrated high reproducibility, with an intraclass correlation coefficient > 0.7 in both cerebral artery and SSS segmentation volumes. This study demonstrates that the large cerebral arteries and SSS can be reproducibly and automatically segmented in fMRI datasets, facilitating the investigation of fluid dynamics in these regions.

Development of SSR markers related to agarwood production and genetic diversity of Aquilaria sinensis (Lour.) Spreng wild populations

Aquilaria sinensis (Lour.) Spreng is an economically important tree that produces agarwood when subjected to mechanical wounding. However, the information regarding its heredity is limited. The breeding of A. sinensis has been hindered due to ambiguity in the sources of germplasm, genetic background, and varietal information. Simple sequence repeat (SSR) markers are ideal for studying genetic diversity and germplasm identification in plants. They offer the advantages of high polymorphism, good reproducibility, and co–dominance. Here, we mined SSR markers within agarwood–inducing genes and used them to explore the genetic diversity among A. sinensis natural germplasm. A total of 407 SSR loci were identified within 92 genes. We designed 96 primer pairs, among which 16 showed polymorphism and were subsequently used to analyze the genetic diversity and population structure of 179 A. sinensis individuals. A total of 107 alleles were identified, with an average of 7 alleles per locus, and their polymorphism information content ranged between 0.424 and 0.769, with an average of 0.569. The analysis of molecular variance revealed that genetic variation within the individuals accounted for 94 % of the total variation, inditing that the variation of A. sinensis is derived from individual variation. Furthermore, the structure analysis indicated that the natural populations of A. sinensis could be theoretically divided into 16 subgroups. The 16 polymorphic SSRs had strong cross–species transferability and distinguished individuals of A. agallochum (Lour.) Roxb. ex Finl. and A. malaccensis Lam. Taken together, these findings provide a useful resource for germplasm identification and molecular marker–assisted breeding of A. sinensis.

Sex-dependent nonlinear Granger connectivity patterns of brain aging in healthy population

BackgroundBrain aging is a complex process that involves functional alterations in multiple subnetworks and brain regions. However, most previous studies investigating aging-related functional connectivity (FC) changes using resting-state functional magnetic resonance images (rs-fMRIs) have primarily focused on the linear correlation between brain subnetworks, ignoring the nonlinear casual properties of fMRI signals. MethodsWe introduced the neural Granger causality technique to investigate the sex-dependent nonlinear Granger connectivity (NGC) during aging on a publicly available dataset of 227 healthy participants acquired cross-sectionally in Leipzig, Germany. ResultsOur findings indicate that brain aging may cause widespread declines in NGC at both regional and subnetwork scales. These findings exhibit high reproducibility across different network sparsities, demonstrating the efficacy of static and dynamic analysis strategies. Females exhibit greater heterogeneity and reduced stability in NGC compared to males during aging, especially the NGC between the visual network and other subnetworks. Besides, NGC strengths can well reflect the individual cognitive function, which may therefore work as a sensitive metric in cognition-related experiments for individual-scale or group-scale mechanism understanding. ConclusionThese findings indicate that NGC analysis is a potent tool for identifying sex-dependent brain aging patterns. Our results offer valuable perspectives that could substantially enhance the understanding of sex differences in neurological diseases in the future, especially in degenerative disorders.

A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity.

The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery (N = 467) or Validation (N = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort (N = 81). Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels > 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.

Tailored portable electrochemical sensor for dopamine detection in human fluids using heteroatom-doped three-dimensional g-C3N4 hornet nest structure

BackgroundThere is widespread interest in the design of portable electrochemical sensors for the selective monitoring of biomolecules. Dopamine (DA) is one of the neurotransmitter molecules that play a key role in the monitoring of some neuronal disorders such as Alzheimer's and Parkinson's diseases. Facile synthesis of the highly active surface interface to design a portable electrochemical sensor for the sensitive and selective monitoring of biomolecules (i.e., DA) in its resources such as human fluids is highly required. ResultsThe designed sensor is based on a three-dimensional phosphorous and sulfur resembling a g-C3N4 hornet's nest (3D-PS-doped CNHN). The morphological structure of 3D-PS-doped CNHN features multi-open gates and numerous vacant voids, presenting a novel design reminiscent of a hornet's nest. The outer surface exhibits a heterogeneous structure with a wave orientation and rough surface texture. Each gate structure takes on a hexagonal shape with a wall size of approximately 100 nm. These structural characteristics, including high surface area and hierarchical design, facilitate the diffusion of electrolytes and enhance the binding and high loading of DA molecules on both inner and outer surfaces. The multifunctional nature of g-C3N4, incorporating phosphorous and sulfur atoms, contributes to a versatile surface that improves DA binding. Additionally, the phosphate and sulfate groups' functionalities enhance sensing properties, thereby outlining selectivity. The resulting portable 3D-PS-doped CNHN sensor demonstrates high sensitivity with a low limit of detection (7.8 nM) and a broad linear range spanning from 10 to 500 nM. SignificanceThe portable DA sensor based on the 3D-PS-doped CNHN/SPCE exhibits excellent recovery of DA molecules in human fluids, such as human serum and urine samples, demonstrating high stability and good reproducibility. The designed portable DA sensor could find utility in the detection of DA in clinical samples, showcasing its potential for practical applications in medical settings.

Symbolic recording of signalling and cis-regulatory element activity to DNA.

Measurements of gene expression or signal transduction activity are conventionally performed using methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm in which such biological activities are stably recorded to the genome. Enhancer-driven genomic recording of transcriptional activity in multiplex (ENGRAM) is based on the signal-dependent production of prime editing guide RNAs that mediate the insertion of signal-specific barcodes (symbols) into a genomically encoded recording unit. We show how this strategy can be used for multiplex recording of the cell-type-specific activities of dozens to hundreds of cis-regulatory elements with high fidelity, sensitivity and reproducibility. Leveraging signal transduction pathway-responsive cis-regulatory elements, we also demonstrate time- and concentration-dependent genomic recording of WNT, NF-κB and Tet-On activities. By coupling ENGRAM to sequential genome editing via DNA Typewriter1, we stably record information about the temporal dynamics of two orthogonal signalling pathways to genomic DNA. Finally we apply ENGRAM to integratively record the transient activity of nearly 100 transcription factor consensus motifs across daily windows spanning the differentiation of mouse embryonic stem cells into gastruloids, an in vitro model of early mammalian development. Although these are proof-of-concept experiments and much work remains to fully realize the possibilities, the symbolic recording of biological signals or states within cells, to the genome and over time, has broad potential to complement contemporary paradigms for how we make measurements in biological systems.

The role of Nuclear Magnetic Resonance (NMR) spectroscopy in cattle metabolism

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical tool that has significantly advanced the understanding of cattle metabolism. Nuclear Magnetic Resonance (NMR) spectroscopy plays a pivotal role in the study of cattle metabolism, offering distinct advantages over other spectrometric methods. NMR spectroscopy is a powerful analytical tool that provides detailed molecular insights by exploiting the magnetic properties of atomic nuclei. Unlike mass spectrometry and infrared spectroscopy, NMR does not require extensive sample preparation or destruction, preserving the integrity of biological samples. This non-invasive nature is particularly beneficial for longitudinal studies in cattle, where metabolic changes over time are of interest. One of the key strengths of NMR spectroscopy is its ability to simultaneously detect and quantify a broad range of metabolites in complex biological matrices, such as blood, urine, and tissue extracts. This comprehensive metabolic profiling is crucial for understanding the biochemical pathways and physiological states in cattle. NMR's high reproducibility and quantitative accuracy further enhance its suitability for metabolic studies, enabling precise monitoring of metabolic fluctuations in response to dietary changes, environmental stressors, or disease conditions. NMR spectroscopy also offers unique advantages in elucidating structural information about metabolites. Through multidimensional NMR techniques, researchers can determine the molecular structure and conformation of metabolites, providing deeper insights into metabolic functions and interactions. This structural elucidation is often challenging with other spectrometric methods, which may lack the resolution or require derivatization of samples. Moreover, NMR spectroscopy's non-destructive nature allows for the analysis of living tissues and in vivo studies, facilitating real-time monitoring of metabolic processes. This capability is instrumental in studying dynamic metabolic responses and adaptations in cattle under different physiological states. Additionally, the development of advanced NMR techniques, such as high-resolution magic angle spinning (HR-MAS) and hyperpolarization, has further expanded the scope of NMR applications in metabolic research. NMR spectroscopy stands out as a superior method for studying cattle metabolism due to its non-destructive approach, comprehensive metabolic profiling, structural elucidation capabilities, and potential for in vivo analysis. These advantages make NMR an indispensable tool in advancing our understanding of cattle metabolism and improving livestock health and productivity. Keywords: Nuclear Magnetic Resonance (NMR), Cattles, Metabolomics.

Reproducibility analysis of bioimpedance-based self-developed live cell assays

Bioimpedance spectrum (BIS) measurements have a great future in in vitro experiments, meeting all the requirements for non-destructive and label-free methods. Nevertheless, a real basic research can provide the necessary milestones to achieve the success of the method. In this paper a self-developed technology-based approach for in vitro assays is proposed. Authors invented a special graphene-based measuring plate in order to assess the high sensitivity and reproducibility of introduced technique. The design of the self-produced BIS plates maximizes the detection capacity of qualitative changes in cell culture and it is robust against physical effects and artifacts. The plates do not influence the viability and proliferation, however the results are robust, stable and reproducible regardless of when and where the experiments are carried out. In this study, physiological saline concentrations, two cancer and stem cell lines were utilized. All the results were statistically tested and confirmed. The findings of the assays show, that the introduced BIS technology is appropriate to be used in vitro experiments with high efficacy. The experimental results demonstrate high correlation values across the replicates, and the model parameters suggested that the characteristic differences among the various cell lines can be detected using appropriate hypothesis tests.

Nanoimprinted Plasmonic Crystals for Cost-Effective SERS Identification of Methylated DNAs.

The development of a cost-effective and rapid assay technique for the identification of DNA methylation is one of the most crucial issues in the field of biomedical diagnosis because DNA methylation plays key roles in human health. The plasmonic crystal-based surface-enhanced Raman spectroscopy (SERS) technique is promising for the realization of such an assay method owing to its capability of generating uniformly enhanced electric fields to achieve high reproducibility and accuracy in SERS assays. However, the time and technical costs of fabricating plasmonic crystals are high, owing to the need for nanofabrication equipment. In this study, we developed nanoimprinted plasmonic crystals for cost-effective and rapid DNA methylation assays. Our plasmonic crystals identified methylated DNA with the 40-base pair adenomatous polyposis coli (APC) gene sequence, which is correlated with cell growth and cancer cells.

Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer.

Tumor necrosis has been reported to represent an independent prognostic factor in colorectal cancer, but its evaluation methods have not been described in sufficient detail to introduce tumor necrosis evaluation into clinical use. To study the potential of tumor necrosis as a prognostic indicator in colorectal cancer, criteria for 3 methods for its evaluation were defined: the average percentage method (tumor necrosis percentage of the whole tumor), the hotspot method (tumor necrosis percentage in a single hotspot), and the linear method (the diameter of the single largest necrotic focus). Cox regression models were used to calculate cancer-specific mortality hazard ratios (HRs) for tumor necrosis categories in 2 colorectal cancer cohorts with more than 1800 cases. For reproducibility assessment, 30 cases were evaluated by 9 investigators, and Spearman's rank correlation coefficients and Cohen's kappa coefficients were calculated. We found that all 3 methods predicted colorectal cancer-specific survival independent of other prognostic parameters, including disease stage, lymphovascular invasion, and tumor budding. The greatest multivariable HRs were observed for the average percentage method (cohort 1: HR for ≥ 40% vs. <3% 3.03, 95% CI, 1.93-4.78; cohort 2: HR for ≥ 40% vs. < 3% 2.97; 95% CI, 1.63-5.40). All 3 methods had high reproducibility, with the linear method showing the highest mean Spearman's correlation coefficient (0.91) and Cohen's kappa (0.70). In conclusion, detailed criteria for tumor necrosis evaluation were established. All 3 methods showed good reproducibility and predictive ability. The findings pave the way for the use of tumor necrosis as a prognostic factor in colorectal cancer.

Application of apical myocardial perfusion quantitative analysis by contrast-enhanced ultrasound utilizing high-frequency linear probe.

Due to insufficient near-field resolution and artifacts, it is challenging to evaluate the left ventricular apical perfusion with phased-array probes. By combining high-frequency linear probe and contrast-enhanced ultrasound (CEUS), imaging of apical myocardial perfusion could be improved. The study aims to evaluate the preliminary application of CEUS by high-frequency linear probes to assess the apical perfusion. The study enrolled retrospectively 91 patients to test the feasibility of the novel method. In protocol 1, patients were stratified into a group with left anterior descending artery (LAD) stenosis (N=40) and a group without LAD stenosis or coronary artery disease (N=41) based on the degree of coronary artery narrowing, quantified by>50% stenosis in coronary angiography. Receiver operating characteristics (ROC) analysis was performed to test the diagnostic value of perfusion parameters. In protocol 2, the reproducibility of high-frequency linear probe in apical perfusion analysis was compared with the conventional phased-array probe in 30 patients. (1) The novel method is feasible in 81(89.01%) patients. (2) In protocol 1, to detect LAD stenosis, the best cut-off of β, T, A, and MBF were 10.32, 3.28, 9.39, and 4.99, respectively. Area under the curve of β, T, A, and MBF were.880,.881,.761, and.880, respectively. (3) In protocol 2, compared with phased-array probe, the quantitative analysis of high-frequency linear probe is of high reproducibility and could get good curve fitting (R2=.29vs. R2=.71, P<.01). Observation of apical perfusion using this method is feasible and quantitative analysis allows an accurate and convenient identification of LAD stenosis. This method provides an alternative for patients who have difficulties in visualizing the apical region with a phased-array probe.

Evaluation of a rapid multi-attribute combinatorial high-throughput UV-Vis/DLS/SLS analytical platform for rAAV quantification and characterization

Recombinant adeno-associated virus (rAAV)-based gene therapies are expanding in their application. Despite progress in manufacturing, current analytical methods for product quantification and characterization remain largely unchanged. Although critical for product and process development, in-process testing, and batch release, current analytical methods are labor-intensive, costly, and hampered by extended turnaround times and low throughput. The field requires more efficient, cost-effective analytical techniques capable of handling large sample quantities to accelerate product and process development. Here, we evaluated Stunner from Unchained Labs for quantifying and characterizing rAAVs and compared it with established analytical methods. Stunner is a combinatorial analytic technology platform that interpolates ultraviolet-visible (UV-Vis) absorption with static and dynamic light scattering (SLS/DLS) analysis to determine capsid and genomic titer, empty and full capsid ratio, and assess vector size and polydispersity. The platform offers empirical measurements with minimal sample requirements. Upon testing hundreds of rAAV vectors, comprising various serotypes and transgenes, the data show a strong correlation with established analytical methods and exhibit high reproducibility and repeatability. Some analyses can be applied to in-process samples from different purification stages and processes, fulfilling the demand for rapid, high-throughput analysis during development. In sum, the pipeline presented streamlines small- and large-batch analytics.